Glaucoma is one of the major eye diseases globally and causes irreversible loss of vision due to the optic nerve damage leading to blindness. It is largely caused by poor filtration of aqueous fluid in the eyeball through the anterior chamber angle. If untreated, it leads to higher internal pressure, permanent nerve damage, and blindness. There are two main types of glaucoma, depending on how the flow of fluid is blocked. These are 1) open-angle glaucoma, which is caused by a gradual hype-functioning of the trabecular meshwork, and 2) angle-closure glaucoma (ACG), which is caused by a change in the position of the iris, which then occludes the drainage channels.
Detection of ACG in the early stage could lead to treatment to arrest its development or slow down the progression. One of the ways of detecting the ACG is anterior chamber angle assessment or measuring the Iridocorneal angle using landmarks such as Schwalbe's line and the Scleral spur. Iridocorneal angle measurements can help to determine suitability of implantable device(s) within the Iridocorneal angle for treating ACG in patients. It is important that these device(s) be implanted in a way that does not harm the corneal endothelium. By ensuring that the largest footprint of the implant would not reach the Schwalbe's line, a physician can confirm that an eye has a configuration suitable for the implant.
In the past, ACG has been diagnosed from optical coherence tomography (OCT) images by finding the scleral spur and assuming a fixed length of the trabecular meshwork (see for example, Lee, R. Y., et al. (2013). “Association between baseline angle width and induced angle opening following prophylactic laser peripheral iridotomy.” Invest Ophthalmol Vis Sci 54(5): 3763-3770). This method was developed when anterior segment OCT used a 1300 nm wavelength, so the scleral spur was generally well seen. The majority of commercial OCT instruments are currently using a wavelength of 840 nm, which has worse penetration through the sclera and much poorer visualization of the scleral spur than an OCT with a 1300 nm wavelength. Some have proposed that since Schwalbe's line is easier to see than the scleral spur in such OCT images, this landmark could be used, again with a fixed length assumed for the trabecular meshwork (see for example, T. Jing, P. Marziliano and H. T. Wong, “Automatic detection of Schwalbe's line in the anterior chamber angle of the eye using HD-OCT images,” Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE, Buenos Aires, 2010, pp. 3013-3016, hereby incorporated by reference).
FIG. 1 shows an exemplary anterior segment high definition optical coherence tomography (HD-OCT) image (referred to herein simply as an OCT image throughout the present disclosure). It is marked to illustrate the locations of the angle recess (the region between the cornea and the iris), the scleral spur (the point where the curvature of the angle wall changes), the corneal endothelium (inner-most layer of cornea), the corneal epithelium (the inner-most layer of cornea), Descemet's membrane (the second innermost layer), and Schwalbe's line (the termination of Descemet's membrane). As illustrated in FIG. 1, the angle recess is obscured in shadow and the scleral spur is not well defined in the OCT image due to the scattering by the sclera. On the other hand, Schwalbe's line, which marks the termination of Descemet's membrane can be identified more clearly in most of the OCT images.
Since the scleral spur is harder to detect, an automatic detection of Schwalbe's line is an alternative landmark to measure the Iridocorneal angle. One of the existing methods to automatically identify the Schwalbe's line (U.S. Pat. No. 8,687,866, hereby incorporated by reference) includes 1) segmenting the posterior corneal surface, 2) extracting the edge of the cornea using linear regression, and 3) using the point at which there is maximum distance between the points on the cornea and the regression line as the location of Schwalbe's line, as shown in FIG. 2. However, there are various limitations associated with this method. Some of them are: 1) in an occurrence of a segmentation error, identifying the Schwalbe's line location based on the maximum distance between the points on the cornea and the regression line is not reliable. For instance, due to the segmentation error, the maximum distance and the regression line may be at different location than the location of the Schwalbe's line. By way of an example, vertical shadows due to eye-lid scans at posterior surface make the segmentation unreliable. Other limitations of this prior-art method are that 2) the method uses a single fitting model, which may not be robust due to variation in anatomy, and 3) the regression line can be biased towards noise (i.e., segmentation error(s)).
Here we describe new methods for automatically detecting the Schwalbe's line that overcomes one or more limitations of the previous/existing methods as discussed above.